Image processing apparatus, image processing method, and program

ABSTRACT

An image processing apparatus for forming an image by superimposing n (n≥2) records on a same region in a recording medium includes: a holding unit configured to hold a threshold matrix characteristic representing a dispersity of a dot pattern of each tone obtained when dithering is performed using a threshold matrix; a setting unit configured to set recording data for n recording scans by dividing image data for the n recording scans based on the threshold matrix characteristic; and a halftoning unit configured to perform dithering using the threshold matrix on the recording data for each of the n records.

BACKGROUND Field of the Disclosure

The present disclosure relates to an image processing technique forforming an image on a recording medium based on image data.

Description of the Related Art

In recent years, printing of image data processed by a personal computerhas been generally performed. The number of tone levels per pixel thatcan be expressed by an image forming apparatus, such as a printer, isoften smaller than the number of tone levels of image data to be treatedby a personal computer. In such a case, halftoning for converting thenumber of tone levels of input image data into the number of tone levelsthat can be expressed by the image forming apparatus. Dithering is knownas one of halftoning techniques. Dithering is a technique fordetermining an output value for each pixel by comparing a pixel value ininput image data with a threshold corresponding to a pixel in athreshold matrix.

Japanese Patent Laid-Open No. 2013-38643 discusses a method in which animage is divided for a plurality of recording scans, and dithering isperformed on recording data for each recording scan by using ablue-noise threshold matrix. In particular, half-tone image data foreach recording scan is generated in consideration of the dispersity ofeach dot pattern obtained by accumulating the recording scans.

However, the dithering cannot convert all tone images into a dot patternwith a high dispersity due to the characteristics of the thresholdmatrix. Accordingly, in the related art, depending on the tone ofrecording data obtained by dividing image data for recording scans, itmay be difficult to obtain a dot pattern for each recording scan as adot pattern with a high dispersity.

SUMMARY

Some embodiments in the present disclosure are directed to generatingimage data capable of outputting a dot pattern with a high dispersityfor a plurality of recording scans.

In some embodiments, an image processing apparatus for forming an imageby superimposing n (n≥2) records on a same region in a recording mediumincludes: a holding unit configured to hold a threshold matrixcharacteristic representing a dispersity of a dot pattern of each tonevalue obtained when dithering is performed using a threshold matrix; asetting unit configured to set recording data indicating an amount ofrecording for n recording scans by dividing image data for the nrecording scans based on the threshold matrix characteristic; and ahalftoning unit configured to perform dithering using the thresholdmatrix on the recording data for each of the n records.

Further features of various embodiments will become apparent from thefollowing description of exemplary embodiments (with reference to theattached drawings).

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are block diagrams each illustrating a configuration ofan image processing apparatus and an image forming apparatus.

FIG. 2 illustrates a configuration example of a recording head 201.

FIG. 3 illustrates a flow of image processing and printing.

FIG. 4 illustrates a relationship between a head and an image formingregion according to a scanning number.

FIGS. 5A, 5B, 5C, and 5D each illustrate characteristics of a thresholdmatrix.

FIG. 6 is a flowchart illustrating recording data setting processing.

FIG. 7 is a flowchart illustrating recording data update processing.

FIG. 8 is a flowchart illustrating halftoning.

FIGS. 9A and 9B each illustrate an advantageous effect obtained byupdating recording data.

FIG. 10 illustrates characteristics of a threshold matrix.

FIG. 11 is a flowchart illustrating a flow of generating a thresholdmatrix.

FIG. 12 is a flowchart illustrating dot pattern generation processing.

FIGS. 13A, 13B, and 13C are conceptual diagrams each illustrating anoutline of dot pattern generation processing.

FIG. 14 is a flowchart illustrating threshold determination processing.

FIGS. 15A, 15B, 15C, and 15D each illustrate characteristics of athreshold matrix.

FIG. 16 is a flowchart illustrating recording data setting processing.

DESCRIPTION OF THE EMBODIMENTS

Some exemplary embodiments will be described below with reference to thedrawings. The following exemplary embodiments do not necessarily limitall embodiments, and not all combinations of the features described inthe exemplary embodiments are necessarily essential for all embodiments.In the following description, the same components are denoted by thesame reference numerals.

In a first exemplary embodiment, print data that can be output from animage forming apparatus employing an inkjet method is generated based onimage data. The image forming apparatus employing the inkjet method isconfigured to perform multi-pass printing processing in which arecording scan is performed n (≥2) times on the same region in arecording medium, and images are superimposed n times, to thereby form afinal image.

(Apparatus Configuration)

FIGS. 1A and 1B are block diagrams each illustrating a configuration ofan image processing apparatus and an image forming apparatus which canbe applied to the first exemplary embodiment. Referring to FIG. 1A, animage processing apparatus 1 and an image forming apparatus 2 areconnected with an interface or a circuit. The image processing apparatus1 corresponds to a personal computer in which a printer driver isinstalled. In this case, each unit in the image processing apparatus 1to be described below is implemented by causing a computer to execute apredetermined program.

FIG. 1B is a block diagram illustrating a hardware configuration of theimage processing apparatus 1. The image processing apparatus 1 includesa central processing unit (CPU) 1001, a read only memory (ROM) 1003, arandom access memory (RAM) 1004, an external storage device 1005, and ageneral-purpose interface 1002. The CPU 1001 controls the overalloperation of an image forming system by using input data and computerprograms stored in the ROM 1003 or the RAM 1004 to be described below. Acase where the CPU 1001 controls the entire image processing apparatuswill now be described by way of example. However, the entire apparatusmay be controlled by causing a plurality of pieces of hardware to sharethe processing. The RAM 1004 includes a storage area for temporarilystoring computer programs or data read from the external storage device1005, and data received from the outside through the general-purposeinterface 1002 to be described below. The RAM 1004 is used as a storagearea for the CPU 1001 to execute various processing, and is also used asa storage area for the CPU 1001 to carry out image processing. In otherwords, the RAM 1004 can provide various storage areas as needed. The ROM1003 stores setting parameters, boot programs, and the like for settingeach unit in the image processing apparatus. The external storage device1005 is a storage device that stores various data, various information,and the like which are required for the CPU 1001 to execute variousprocessing. The external storage device 1005 is, for example, a harddisk drive (HDD). The general-purpose interface 1002 is an interface forcommunicating with an external apparatus (the image forming apparatus 2in this case). The general-purpose interface 1002 is, for example, auniversal serial bus (USB) interface.

FIG. 1A illustrates a logical configuration of the image processingapparatus 1. The image processing apparatus 1 stores color image data tobe printed that is input from the input terminal 101 (hereinafterreferred to as input image data) in an input image buffer 102. The inputimage data includes three color components of red (R), green (G), andblue (B).

A color separation processing unit 103 separates input image data ofeach color into image data corresponding to the color of each colormaterial included in the image forming apparatus 2. The color separationprocessing unit 103 refers to a color separation look-up table (LUT)104. In the present exemplary embodiment, the input image data of ROBcolors is separated into image data corresponding to the colors of fourcolor materials (i.e., cyan (C), magenta (M), yellow (Y), and black(K)).

The recording data setting unit 105 divides image data, which isobtained after color separation processing and corresponds to the colorsof each color material obtained from the color separation processingunit 103, for recording scans, and converts the recording scans intorecording data representing the amount of recording per recording scan.The recording data according to the present exemplary embodimentindicates the amount of ink used for printing by each scan. Therecording data setting unit 105 uses a threshold matrix characteristicLUT 106. The threshold matrix characteristic LUT 106 is a look-up table(LUT) that holds tones in a threshold matrix 108 used by the halftoning(HT) processing unit 107 (also referred to herein as the “halftoningunit 107”) and the dispersities of each dot pattern in such a mannerthat the tones are linked to the dispersities. Details of recording datasetting processing and a threshold matrix characteristic LUT will bedescribed below.

The halftoning unit 107 executes dithering on recording data per scan ofeach color obtained by the recording data setting unit 105, and convertsthe recording data into half-tone image data with a small number of tonelevels. The halftoning unit 107 executes dithering using the thresholdmatrix 108. The threshold matrix 108 includes blue noisecharacteristics. Dithering will be described in detail below. Thehalf-tone image data is stored in a half-tone image storage buffer 109,and is then output to the image forming apparatus 2 from an outputterminal 110.

The image forming apparatus 2 causes a recording head 201 to movevertically and horizontally relative to a recording medium 202 based onthe half-tone image data of each color received from the imageprocessing apparatus 1, thereby forming an image on the recordingmedium. The recording head 201 employs an inkjet method and includes oneor more recording elements (nozzles).

FIG. 2 illustrates a configuration example of the recording head 201. Inthe present exemplary embodiment, as described above, four types of ink(i.e., cyan (C), magenta (M), yellow (Y), and black (K)) are mounted onthe recording head 201. A head control unit 204 controls a moving unit203 to move the recording head 201. A conveyance unit 205 conveys therecording medium 202 under control of the head control unit 204.

FIG. 4 illustrates multi-pass printing performed by the image formingapparatus 2. FIG. 4 illustrates a nozzle row corresponding to a certaincolor. The nozzle row includes 16 nozzles. When a scanning number k=1,four nozzles located at a position corresponding to ¼ of the length of anozzle lower end perform recording on a region A. When recording isperformed while the recording head is moved in a scanning direction,paper is fed by ¼ of the nozzle length in a direction perpendicular tothe scanning direction of the recording head. Next, when the scanningnumber k=2, four nozzles perform recording on the region A and therecording medium is moved. This operation is repeated to thereby form animage on the region A by four scanning operations. In the presentexemplary embodiment, such 4-pass printing will be described by way ofexample.

An ink color selection unit 206 selects ink corresponding to half-toneimage data to be printed from the ink mounted on the recording head 201based on the half-tone image data for each scan corresponding to eachcolor formed by the image processing apparatus 1.

Next, processing to be executed by the image processing apparatus 1 andthe image forming apparatus 2 applicable to the present exemplaryembodiment including the functional configuration described above willbe described.

FIG. 3 is an overall operation flow up to image printing based on inputimage data. In the following description, each operation is denoted by“S”. First, in S301, input image data on each color input by the inputterminal 101 is stored in the input image buffer 102. The input imagedata used herein refers to data on three color components of red (R),green (G), and blue (B). Each piece of input image data is 8-bit data.Any one of pixel values 0 to 255 is stored in each pixel constituting animage indicated by the input image data.

In S302, the color separation processing unit 103 separates RGB colorsindicated by the input image data for each of the CMYK colors by usingthe color separation LUT 104. In the present exemplary embodiment, imagedata subjected to the color separation processing is treated as 8-bitdata, but instead 8-bit or more data may be converted into a number oftone levels. The recording head 201 according to the present exemplaryembodiment holds four types of ink of CMYK. Accordingly, the input imagedata of RGB colors is converted into four pieces of image data of CMYKcolors.

In S303, the recording data setting unit 105 acquires the thresholdmatrix characteristic LUT 106. The threshold matrix characteristic LUTwill be described in detail below.

In S304, the recording data setting unit 105 initializes the scanningnumber k. In the present exemplary embodiment, an initial value for thescanning number k is 1, and the scanning number k is incremented by 1every processing loop.

The following S305 to S310 are performed for each of the CMYK colors.Although processing for cyan (C) will now be described by way ofexample, the same processing is also performed on the other three typesof color material (i.e., magenta (M), black (K), and yellow (Y)).

In S305, the recording data setting unit 105 sets Ycut(k) representing aY-coordinate as an image data cut-out position obtained after colorseparation. Ycut(k) represents the image data cut-out position obtainedafter color separation in the scanning number k and corresponds to anozzle upper-end coordinate. A method for setting the image data cut-outposition Y-coordinate Ycut(k) obtained after color separation will bedescribed with reference to FIG. 4.

As described above, the present exemplary embodiment illustrates 4-passprinting, and one pass is recorded using a nozzle ¼. When the scanningnumber k=1, the image data cut-out position Ycut, which is obtainedafter color separation and which corresponds to the nozzle upper-endcoordinate, is −12.

When the image data cut-out position Ycut(k) after color separation isgeneralized, the following formula is given assuming that the number ofnozzle rows is Nzzl, the number of passes is Pass, and the scanningnumber is k.

Ycut(k)=−Nzzl+(Nzzl/Pass)×k   (1)

As described above, when Ycut(k) is set, the recording data setting unit105 then sets recording data for each scan based on the acquiredthreshold matrix characteristic LUT and the image data which is obtainedafter color separation and which corresponds to each color. Theprocessing for setting the recording data will be described in detailbelow.

Next, in S307, the halftoning unit 107 performs dithering using thethreshold matrix on the recording data for each recording scan. Thehalftoning according to the present exemplary embodiment converts therecording data (8-bit) represented by 256 tones into a binary value. Thehalftoning will be described in detail below. In S308, the halftoneimage is stored.

In S309, band data which is stored in the half-tone image storage buffer109 and in which the longitudinal direction corresponds to the number ofnozzles (Nzzl) and the lateral direction corresponds to an image X size(W) is output from the image output terminal 110.

In S310, the image forming apparatus 2 which has received the half-toneimage data selects ink colors that match the half-tone image data andstarts a printing operation. Specifically, the recording head 201performs main scanning once for driving each nozzle at predetermineddriving intervals and recording an image on a recording medium, whilemoving from left to right with respect to the recording medium. Further,when the main scanning is finished, feeding of the recording medium iscarried out once.

In S311, it is determined whether all scans are finished. If all theoperations are finished, a series of image formation processing iscompleted. If all the operations are not finished, in S312, the scanningnumber k is updated and the processing returns to S305. Thus, all theprocessing is terminated if in S311 it is determined that all scans arefinished.

Dithering characteristics and the threshold matrix characteristic LUTwill now be described in detail. FIG. 5A illustrates an example of aninput image. The input image includes 4 pixels×4 pixels, and a pixelvalue 153 is stored in each pixel. FIG. 5B illustrates an example of athreshold matrix. In the threshold matrix, different values are storedas thresholds respectively corresponding to the pixels. In thedithering, the pixel value of each pixel is compared with the thresholdcorresponding to each pixel. When the pixel value is greater than thethreshold, “1” is output. When the pixel value is smaller than thethreshold, “0” is output. FIG. 5C illustrates an output image obtainedby performing dithering on the input image. The output image illustratedin FIG. 5C represents a dot pattern obtained when a tone 153 is set. Inthis manner, the dispersity of each dot pattern is determined based onthe arrangement of the thresholds in the threshold matrix.

A graph of FIG. 5D illustrates an example of the dispersitycorresponding to each tone in the threshold matrix. A horizontal axisrepresents a tone (pixel value), and a vertical axis represents adispersity evaluation value. When dithering is performed on an imagehaving a certain tone by using the threshold matrix, a dot patternobtained as a result of the dithering is subjected to Fourier transformand a weighting sum P of powers is calculated as a dispersity evaluationvalue. The larger the dispersion value evaluation value, the lower thedispersion, and the smaller the value, the higher the dispersion value.As illustrated in FIG. 5D, the dispersity for the tones in the thresholdmatrix varies finely with respect to the tone. In the dithering usingthe threshold matrix, it is difficult to achieve the dot pattern with ahigh dispersity for all tones. This is because a dot pattern in thevicinity of a certain tone is determined by adding or deleting dots toor from the dot pattern in a certain tone, thereby designing thethreshold matrix.

For example, in the case of using a known Void-and-Cluster method, afterthe dot pattern for the tone initially set is determined, positionswhere the dots are sequentially added according to a predetermined ruleare determined and the dot pattern for the tone located closer to ashadow than the initial tone is determined. Further, the dots of the dotpattern for the initial tone are sequentially deleted to therebydetermine the dot pattern for the highlight-side tone. Accordingly, thedot pattern for the initial tone has no constraint on the dotarrangement, and a high-dispersion dot arrangement can be arbitrarilyselected. However, a dot arrangement other than the dot pattern for theinitial tone is constrained by the dot pattern for the initial tone. Asdescribed above, not only in the Void-and-Cluster method describedabove, but also in designing of a threshold matrix, a dot pattern of acertain input value is constrained by the already determined dotpattern, and a dot pattern with a high dispersion cannot always beobtained.

Accordingly, in the present exemplary embodiment, the dispersityevaluation value of a dot pattern for each tone of the threshold matrixillustrated in FIG. 5B is held as the threshold matrix characteristicLUT. Further, when dithering using the threshold matrix is performed,image data obtained after color separation is divided for each recordingscan so that the tone can be converted into a dot pattern with thehighest dispersion possible.

The recording data setting processing will be described in detail below.In the present exemplary embodiment, the image data obtained after colorseparation is equally divided for each recording scan, and the recordingdata for each recording scan is updated based on the characteristics ofthe threshold matrix.

FIG. 6 is a flowchart for recording data setting processing to beexecuted by the image processing apparatus 1. The CPU 1001 reads aprogram that can implement the flowchart illustrated in FIG. 6 andexecutes the program, thereby implementing each configuration(function). In the processing illustrated in FIG. 6, assuming that atarget nozzle position ny and an image X address are set as iterationvariables, recording data is set in each pixel included in a bandcorresponding to the number of nozzles (Nzzl)×the X size (W) of theimage.

First, in S601, the recording data setting unit 105 initializes thetarget nozzle position ny to be subjected to the recording data settingprocessing. Specifically, ny=0 is set. In S602, the recording datasetting unit 105 acquires a pass number p from the nozzle position ny.The pass number p is acquired using the following formula (2). In theformula (2). Pass represents the number of print passes, int(x)represents a function which returns the largest integer smaller than x,and the number of nozzles Nzzl is an integral multiple of the number ofprint passes.

p=int(ny/(Nzzl/Pass))+1   (2)

In S603, the recording data setting unit 105 determines whether thetarget nozzle position ny falls within a region of an image Y address.Specifically, it is determined whether Ycut(k)+ny is equal to or greaterthan 0 and less than a Y-size H. If the target nozzle position ny fallswithin the region of the image Y address, the processing proceeds toS605. On the other hand, if the target nozzle position ny falls outsideof the region of the image Y address, the processing proceeds to S604and recording data M=0 is set. After that, the processing proceeds toS611.

In S605, the recording data setting unit 105 initializes the X-addressof the image to be subjected to the recording data setting processing.Specifically, X=0 is set.

In S606, the recording data setting unit 105 acquires image data D,which corresponds to the image address (X,Ycut(k)+ny), after colorseparation. Specifically, in this case, the pixel value of each pixelincluded in one line corresponding to the target nozzle is acquired.

In S607, the recording data setting unit 105 calculates the recordingdata M when pixel values are equally divided based on the pass number p,the number of print passes Pass, and the image data D obtained aftercolor separation. Specifically, the recording data M is calculatedaccording to the following formula (3).

M=int(D×p/Pass)   (3),

where the number of print passes Pass is 4. The pass number is a numberindicating a recording scan that is one of the four passes and takes anyone of values 1 to 4.

In S608, the recording data setting unit 105 determines whether the passnumber p is equal to the number of print passes Pass. In other words,the recording data setting unit 105 determines whether the pass numberallocated to the target nozzle matches the pass number corresponding toa last pass. Since four-pass printing is carried out in the presentexemplary embodiment, assume that it is determined whether the passnumber is 4. If the pass number does not correspond to the last pass,the processing proceeds to S609 to update the recording data based onthe characteristics of the threshold matrix. The processing of S609 willbe described in detail below. On the other hand, if the pass numbercorresponds to the last pass, the processing proceeds to S610 withoutperforming the update processing of S609. In other words, when P=Pass,the image data D obtained after color separation is set as the recordingdata M. The reason for this will be described below.

In S610, the recording data setting unit 105 determines whether theimage X address indicates an image end. Specifically, it is determinedwhether X is equal to W−1. When X=W−1 does not hold, in S612, the imageaddress X is updated with X+1 and the processing returns to S606. WhenX=W−1 holds, the processing proceeds to S611.

In S611, the recording data setting unit 105 determines whether thenozzle position ny indicates a nozzle end. Specifically, the recordingdata setting unit 105 determines whether the nozzle position ny is equalto Nzzl−1. When ny=Nzzl−1 does not hold, in S613, the nozzle position nyis updated with ny+1 and the processing returns to S602. When ny=Nzzl−1holds, the recording data is set to each pixel of band datacorresponding to the number of nozzles (Nzzl)×the X-size (W) of theimage, and the processing is terminated.

Next, processing for updating the recording data M to be executed by therecording data setting unit 105 in S609 will be described in detail. Inthe processing for updating the recording data M, if recording data M′with which a dot pattern with a higher dispersion than that of therecording data M can be obtained falls within a search area, therecording data M is updated with M′ based on the characteristics of thethreshold matrix.

FIG. 7 is a flowchart illustrating a flow of processing for updating therecording data M in S609. The CPU 1001 reads a program that canimplement the flowchart illustrated in FIG. 7 and executes the program,thereby implementing each configuration (function).

In S701, temporary recording data tmp_M is initialized. The temporaryrecording data tmp_M is a variable for holding a candidate for recordingdata with which a high-dispersion dot pattern can be obtained in loopprocessing of S704 to S709, to be described below. In S710 after theloop processing, recording data finally held as tmp_M is set as theupdated recording data M′.

In S702, a variable lim for specifying a search area for M′ is acquired.In the present exemplary embodiment, lim=16 is set. FIG. 5D illustratesa relationship between the recording data M and the variable lim. Theupdated recording data M′ is set by searching for recording data with ahighest dispersion (with a small dispersity evaluation value) within arange from a lower limit value M−lim to an upper limit value M+lim. Thevariable lim may vary depending on the input value. For example, thevariable lim is set to about 5 to 10% of the image data D, therebypreventing overlapping of with a low-density search area, such as ahighlight region.

In S703, a variable Δm for indicating the target recording data in thesearch area for the recording data is initialized. Assume herein that aninitial value for the variable Δm is Δm=−lim.

In S704, a dispersity evaluation value P for the temporary recordingdata tmp_M is acquired with reference to the threshold matrixcharacteristic LUT 106 acquired in S303 described above. Similarly, inS705, a dispersity evaluation value P′ corresponding to recording dataM+Δm is acquired with reference to the threshold matrix characteristicLUT 106.

In S706, it is determined whether P′ is smaller than P. If P′ is smallerthan P, the processing proceeds to S707 to update the temporaryrecording data tmp_M with M+Δm, and then the processing proceeds toS708. On the other hand, if P′ is equal to or greater than P, S707 isomitted and the processing proceeds to S708.

In S708, it is determined whether processing of S704 to S707 has beenperformed on all recording data on search areas M−lim to M+lim.Specifically, it is determined whether the variable Δm is equal to lim.If the variable Δm is not equal to lim, in S709, the variable Δm isupdated with Δm+1 and the processing returns to S704. If the variable Δmis equal to lim, it is determined that processing has been performed onall recording data, and the processing proceeds to S710.

In S710, as described above, the recording data finally held as tmp_M isset as the updated recording data M′, and then the processing isterminated.

Halftoning in S307 will be described in detail. In the present exemplaryembodiment, recording data obtained in the previous recording scan (k=1when scanning number k=2) is held as constraint information C. Theconstraint information C is information having a correlation with thepossibility that dots are already located at the same position in arecording scan immediately before the recording scan to be processed.When the constraint information C indicates a large value, it is highlylikely that a dot is already located. When the constraint information Cindicates a small value, it is likely that a dot is not located yet.Half-tone image data for each scanning number is generated using theconstraint information C in addition to a threshold Th obtained from thethreshold matrix and the recording data M set in S306.

FIG. 8 is a flowchart illustrating a flow of half processing to beperformed by the halftoning unit 107. The CPU 1001 reads a program thatcan implement the flowchart illustrated in FIG. 8 and executes theprogram, thereby implementing each configuration (function). Also, inthe halftoning illustrated in FIG. 8, like in the setting of recordingdata illustrated in FIG. 6, processing is performed on each pixel in aband corresponding to the number of nozzles (Nzzl)×the X size (W) of theimage. In this processing, an image address (X, Y) is used for aniteration variable.

First, in S801, the halftoning unit 107 initializes the image address(X, Y) to be processed. Specifically, X=0 and Y=Ycut(k).

In S802, the halftoning unit 107 acquires a threshold Th (X, Y)corresponding to the image address (X, Y) by referring to the thresholdmatrix 108. Similarly, in S803, the halftoning unit 107 acquiresconstraint information C (X, Y) corresponding to the image address (X,Y). When the scanning number k=1 at the time of starting processing, aninitial value “0” is substituted into all the constraint information C(X, Y). Accordingly, when the scanning number k≥2, the information isupdated with significant information.

In S804, the halftoning unit 107 determines whether the constraintinformation C (X, Y) is greater than the threshold Th (X, Y).

If the constraint information C (X, Y) is greater than the threshold Th(X, Y), the processing proceeds to S805 to set OFF to the dotcorresponding to the image address (X, Y). The granularity of a dotpattern including dots accumulated by continuously locating a dot at thesame position deteriorates. Therefore, according to the constraintinformation C, it is highly likely that a dot is located immediatelybefore, and thus no dot is located at the image address (X, Y).

On the other hand, if the constraint information C (X, Y) is equal to orless than the threshold Th (X, Y), the processing proceeds to S806. InS806, recording data M (X, Y) corresponding to the image address (X, Y)is acquired. In S807, the halftoning unit 107 determines whether therecording data M (X, Y) is greater than the threshold Th (X, Y).

If the recording data M (X, Y) is greater than the threshold Th (X, Y),the processing proceeds to S808 to turn on the dot corresponding to theimage address (X, Y). Specifically, when the threshold Th (X, Y) isgreater than the recording data obtained in the previous recording scanand is smaller than the recording data obtained in the recording scan tobe processed, a dot is located.

On the other hand, if the recording data M (X, Y) is equal to or lessthan the threshold Th (X, Y), the processing proceeds to S805 to turnoff the dot corresponding to the image address (X, Y).

Next, in S809, it is determined whether the processing of S801 to S808has been executed on addresses (0, 0) to (W−1, Nzzl−1) within the band.Specifically, it is determined whether half-tone data corresponding tonozzles 0 to 15 illustrated in FIG. 4 is already created.

If it is determined that the processing within the band is not finished,the image address (X, Y) is updated in S810 and the processing returnsto S802. On the other hand, if it is determined that the processingwithin the band is finished, the processing proceeds to S811. In S801 toS810 described above, pixel values indicating all addresses (pixels) aredetermined to thereby determine a dot pattern formed by each recordingscan. The half-tone image data is stored in the half-tone image storagebuffer.

In S811, the constraint information C is updated. The constraintinformation C (X, Y) obtained by updating the recording data M (X, Y) isstored in a constraint information buffer (not illustrated). In S812,the constraint information C is shifted by LF (paper feed amount). Thereason for shifting the data by the paper feed amount LF is that thehalf-tone image data formed in the next scanning number is shiftedrelatively by the paper feed amount LF on the recording medium. However,“0” is substituted into the constraint information C corresponding to anumber of nozzles (e.g., 16 nozzles; in the case of four-pass, fournozzles) located at a lower end LF after shift.

The constraint information C updated and shifted in S811 and S812 isused for performing halftoning on the recording data corresponding tothe next scanning number (the scanning number k=2 which is next to thescanning number k=1). Specifically, the constraint information generatedbased on the half-tone image data corresponding to the scanning number kis held as constraint information used for performing halftoning on therecording data corresponding to the scanning number k+1.

Heretofore, recording data for each recording scan has been generated byequally dividing an image for each recording scan so that the usage rateof nozzles can be equalized and unevenness due to deflection of dots canbe reduced. For example, if the pixel value of a certain pixel in animage is 96 and the number of print passes is 4, M=96/4=24 is equallyallocated to the recording data in each pass. This indicates that, forexample, a dot pattern recorded by a recording scan in a first passcorresponds to the dispersity evaluation value corresponding to a tone24 of a threshold matrix. Since pixel values are divided withoutconsidering the characteristics of the threshold matrix, the dispersityevaluation value for each recording scan is not necessarily high.However, if a positional deviation occurs in each recording scan, whenthe dispersity of a dot pattern in each recording scan is low, adeterioration of granularity and a density unevenness occur.Accordingly, in some embodiments of multi-pass printing, dot patterns inoverlapping recording scans have the highest dispersity possible.Therefore, in the present exemplary embodiment, as described above, theimage is divided for each recording scan based on the characteristics ofthe threshold matrix so as to increase the dispersity of the dot patternin each recording scan.

FIG. 9A is an enlarged view of a part of FIG. 5D. For example, thedispersity evaluation value obtained from the dot pattern of therecording data M=21 is smaller than the dispersity evaluation valuecorresponding to the dot pattern of the recording data M=24 allocated tothe pass number 1. In other words, a dot pattern formed when therecording data M=21 is allocated to the pass number 1 has a higherdispersion than that of a dot pattern formed when the recording dataM=24 is allocated to the pass number 1. In the present exemplaryembodiment, when the recording data M′ with which a dot pattern with ahigher dispersion can be obtained in a predetermined search rangecentered on the recording data obtained by equally dividing the imagedata obtained after color separation for each recording scan is set, therecording data is updated. FIG. 9B is a diagram illustrating therecording data and search area allocated to each recording scan and therecording data to be updated. Based on the characteristics of thethreshold matrix, the recording scan of the pass number 1 is updatedwith M=21, the recording scan of the pass number 2 is updated with M=44,and the recording scan of the pass number 3 is updated with M=77.However, in the present exemplary embodiment, in order to prevent thedensity from varying due to updating of recording data, updating ofrecording data based on the characteristics of the threshold matrix isnot performed on the recording scan of the pass number 4, which is thefinal pass number.

In this manner, according to the present exemplary embodiment, imagedata obtained after color separation and corresponding to each color isdivided for a plurality of recording scans based on the threshold matrixcharacteristic LUT, thereby setting recording data for each recordingscan. Thus, a dot pattern for each recording scan, except for the finalscan, can be formed with a higher dispersion. Consequently, imageformation with less variation in density or granularity due to apositional deviation of dots can be achieved. In the first exemplaryembodiment described above, the threshold matrix characteristic is heldas a LUT, and the recording data M is updated with reference to thethreshold matrix characteristic. However, the recording data may be setwith reference to the LUT in which the image data obtained after colorseparation and the recording data M′ for each recording scan arecorrelated with each other. The LUT in which the image data obtainedafter color separation and the recording data M′ are correlated witheach other can be created by performing processing of S606 and S607 onthe image data obtained after color separation for 0 to 255 in advance.

Further, in the first exemplary embodiment, halftoning is performed onthe recording data by using the recording data for the previousrecording scan as constraint information. Thus, even when dithering isperformed on the recording data for each recording scan by using thesame threshold matrix, a dot pattern for each recording scan can begenerated so that overlapping of dots can be prevented and thedispersity of accumulated dot patterns is increased. However, therecording data may be updated in consideration of the dispersity of asingle dot pattern for each recording pass. For example, dispersityevaluation values for accumulated dot patterns in each pass number and asingle dot pattern are calculated, and a weighting sum P_all of thedispersity evaluation values is obtained. Further, in S809, therecording data M may be updated with M′ so that P_all decreases.

In the present exemplary embodiment, a configuration in which nozzlesare arranged in a row in a direction (main scanning direction) in whicha recording medium is conveyed is described for ease of explanation.However, the number of nozzles and the arrangement of nozzles are notlimited to those in this example. For example, nozzles having differentdischarge amounts with the same density and the same color may be used,or nozzles with the same discharge amount may be arranged in a pluralityof rows. Further, a configuration in which nozzles are arranged in azig-zag manner may be employed. While the present exemplary embodimentillustrates an example that has four colors of ink (i.e., cyan (C),magenta (M), yellow (Y), and black (K)) as the configuration of therecording head 201, the type of ink is not particularly limited.Low-density ink, such as light cyan and light magenta; particular colorink, such as red and green; and white ink may also be used. In addition,colorless and transparent clear ink and metallic ink may also be used.

Further, the input image data indicates an image in RGB colors, but thetype of an image is not particularly limited. Image data indicating amonochrome image or an image in CMYK colors may be used. The input imagedata may include information other than colors, such as an imageincluding gloss information. The number of bits of the color separationLUT is not limited to this example. Alternatively, a method other thanthe LUT may be used and, for example, a matrix operation and anyapplicable formula may be used.

Further, the present exemplary embodiment illustrates an example wherethe image processing apparatus 1 includes software for implementingprocessing by causing the CPU 1001 to execute a predetermined program.However, a part or the whole of the configuration of the imageprocessing apparatus 1 may be implemented using dedicated imageprocessing circuit. The image processing apparatus 1 may be incorporatedin the image forming apparatus 2.

The first exemplary embodiment described above illustrates a method forupdating the equally-divided recording data with the recording data M′with which the arrangement of dots with a higher dispersion can beobtained within the width of the recording data centered on the equallydivided recording data. In a second exemplary embodiment, a method fordesigning a threshold matrix assuming that the threshold matrix isreferenced when recording data for each recording scan is set will bedescribed.

FIG. 10 illustrates a dispersity evaluation value for each tone of thethreshold matrix created according to the second exemplary embodiment.The threshold matrix is created in such a manner that recording data inwhich dot patterns have a relatively-high dispersion are notconcentrated in a specific tone range as indicated by a threshold matrixcharacteristic 1101. Further, a method for determining the variable limfor using the threshold matrix created by the method described in thesecond exemplary embodiment will be described. The illustration of partsin the second exemplary embodiment that are the same as those in thefirst exemplary embodiment is simplified or omitted.

Processing for creating a threshold matrix having characteristics asillustrated in FIG. 10 will be described below.

FIG. 11 is a flowchart illustrating a flow of processing for creating athreshold matrix according to the present exemplary embodiment. In thepresent exemplary embodiment, assume that the image processing apparatus1 illustrated in FIGS. 1A and 1B creates the threshold matrix and theCPU 1001 reads a program that can implement the flowchart illustrated inFIG. 11 and executes the program. However, the processing for creatingthe threshold matrix may be executed by another image processingapparatus other than the image processing apparatus that performssetting of recording data and halftoning. In S1201, a matrix creationunit (not illustrated) acquires, as high-dispersion tones, a pluralityof tones M1 to Mn with which high-dispersion dot patterns are to becreated. In this case, “n” represents the number of tone levels toobtain a high dispersion. The plurality of tones M1 to Mn specifiedherein are desirably tones set at predetermined intervals. In the caseof creating a threshold matrix having characteristics illustrated inFIG. 11 described above, n=7, M1=32, M2=64, M3=96, M4=128, M5=160,M6=192, and M7=224 are set. Further, a minimum value M_min and a maximumvalue M_max that can be taken by each tone are represented by M0=M_minand M8=M_max, respectively. In the present exemplary embodiment,recording data is represented by 256 tones (8-bit), so that M_max=255holds.

In S1202, dot numbers d1 to dn, respectively corresponding to thehigh-dispersion tones M1 to Mn, are acquired. For example, a dot numberdx (x is 1 to n) can be calculated by the following formula (4) from thetone Mx. In this case, “w” represents the X-size of the threshold matrixand “h” represents the Y-size of the threshold matrix.

dx=w×h×Mx/M ⁻max   (4)

In S1203, dot patterns A1 to An, respectively corresponding to thehigh-dispersion tones M1 to Mn, are generated. A method for generatingthe dot patterns will be described in detail below.

In S1204, based on the dot patterns A1 to An of the high-dispersiontones, dot patterns corresponding to all tones other thanhigh-dispersion tones are determined. Further, a threshold correspondingto each position in the threshold matrix (each address within thematrix) is determined to thereby generate the threshold matrix. A methodfor generating the dot patterns will be described in detail below.

A method for generating the dot patterns A1 to An, respectivelycorresponding to the high-dispersion tones M1 to Mn, in S1203 will bedescribed in detail below. There is no need to generate the dot patternA0 corresponding to M0=M_min by the following method, and any applicablemethod may be used as long as data with the number of dots of “0” isset. Similarly, the dot pattern A8 corresponding to M8=M_max is data inwhich dots are arranged in all pixels.

FIG. 12 is a flowchart illustrating a method for generating the dotpatterns A1 to An, respectively corresponding to the high-dispersiontones M1 to Mn, in S1203. In the processing flow illustrated in FIG. 12,an iteration variable I is changed from I=1 to I=n, to thereby generatethe dot patterns A1 to An.

First, in S1301, the matrix creation unit initializes the iterationvariable I. Specifically, I=1 is set.

In S1302, it is determined whether the dot pattern corresponding to anyone of the high-dispersion tones M is already determined. Specifically,it is determined whether the iteration variable I is equal to aninitialized value (I=1 in the present exemplary embodiment).

When I=1, the processing proceeds to S1303 to arrange dI=d1=w×h×M1/M_maxdots with a high dispersion. For example, a number of dots correspondingto the dot number dI are arranged with a high dispersion according to aninitial pattern creation method in the known Void-and-Cluster method.Alternatively, the dot arrangement may be determined using a known errordiffusion method for the tone which is determined in such a manner thata number of dots corresponding to the dot number dI are arranged. InS1302, if it is determined that I=1 does not hold, the processingproceeds to S1304. In S1304 and S1305, a high-dispersion dot pattern isdetermined under a constraint of the determined dot pattern. Detailsthereof will be described below.

In S1306, the determined dot pattern is stores as a dot pattern AIcorresponding to a high-dispersion tone Mx in a dot pattern buffer (notillustrated).

Next, in S1307, it is determined whether I=n holds. If I=n holds, allthe dot patterns A1 to An respectively corresponding to thehigh-dispersion tones M1 to Mn acquired in S1201 are already generated,and thus the processing is terminated. If I=n does not hold, theiteration variable I is updated with I+1 and the processing returns toS1302.

An outline of the processing in S1304 and S1305 will be described withreference to conceptual diagrams illustrated in FIGS. 13A to 13C. FIG.13A is a diagram in which dots arranged with a high dispersion in S1303are represented by black circles. In S1304, dI-dI′ dots are newlyarranged for a dot arrangement AI′ arranged in a preceding iterationvariable I′ (I′=1 when I=2). Assuming herein that dI=18 and dI′=9, inS1304, dI-dI′=18−9=9 dots are arranged at random locations asrepresented by white circles illustrated in FIG. 13B.

Next, in S1305, the dots newly arranged in S1304 are rearranged to forma high-dispersion dot pattern. Specifically, only the dots representedby white circles in the dot pattern illustrated in FIG. 13B arerearranged, to thereby form a high-dispersion dot pattern as illustratedin FIG. 13C. As a method for rearranging the dots, like in the knownVoid-and-Cluster method, a void region in which the dot density is lowand a clustered-dot pattern in which the dot density is highest aresearched using a Gaussian filter, and the clustered-dot pattern is movedto the void region. In this case, however, in the clustered-dot pattern,only the locations where the dots are newly arranged in S1304 (i.e.,only the locations of the dots represented by white circles illustratedin FIGS. 13B and 13C) are searched and moved.

In the Void-and-Cluster method, dot patterns for each tone aresequentially determined from the initial pattern. Accordingly, in thetones other than the tone for the initial pattern, the arrangement canbe made only within the range of one dot, which makes it difficult tocontrol the dispersity of a dot pattern in a specific tone.

On the other hand, in the method described above, dot patterns forspecific high-dispersion tones M1 to Mn are determined. Accordingly, inthe case of determining the dot patterns for the high-dispersion tonesM1 to Mn, dI-dI′ dots can be arbitrarily arranged, so that the degree offreedom of dot arrangement is higher than that in the related art, andthus a high-dispersion dot pattern can be generated. The thresholddetermination processing in S1204 will be described in detail below. Asdescribed above, a dot pattern in a target tone to be processed isconstrained by the dot pattern of the tone already determined.Specifically, when a dot pattern with a dot number d and a dot number d′(where d+1<d′) is determined, a dot newly arranged when d+1 is any oneof the dots arranged in the dot number d′.

This configuration will be described in detail with reference to FIGS.13A to 13C. In a dot arrangement when d=10, any one of the dotsrepresented by the white circles is added to the dot patterns dotpatterns) represented by black circles in FIG. 13C.

In the threshold determination processing according to the presentexemplary embodiment, a total dot number s is set as an iterationvariable and is changed from the total dot number s=1 to s=w×h, therebydetermining the dot arrangement in which dots are arranged at all w×hpixel locations in the threshold matrix (addresses within the matrix).

FIG. 14 is a flowchart illustrating a flow of threshold determinationprocessing in S1204. First, in S1501, the matrix creation unitinitializes the total dot number s. Specifically, s=1 is set.

Next, in S1502, dot patterns A′ and A are acquired. The dot pattern A′is a dot pattern in a total dot number s−1. The dot pattern A isacquired in such a manner that dot patterns in which the number of dotsis equal to or greater than “s” is extracted from the dot patterns A0 toA8 generated in S1203, and the dot pattern with a minimum number of dotsis acquired as the dot pattern A.

Next, in S1503, one of the dot locations where dots turn on in the dotpattern A and turn off in the dot pattern A′ is selected and theselected dot is turned on. For example, in the Void-and-Cluster method,the dot location where the dot density is lowest is searched from thedot locations where dots turn on in the dot pattern A and turn off inthe dot pattern A′ by using a Gaussian filter, and the searched dot isturned on.

In S1504, the threshold “s” is allocated to the address within thematrix corresponding to the dot location of the dot turned on in S1503.

Next, in S1505, it is determined whether s=w×h holds. If s=w×h holds,the processing proceeds to S1506 and the threshold is normalized toobtain the threshold matrix. Specifically, a threshold Th′ that isnormalized by the following formula (5) is calculated from the thresholdTh allocated to the address within each matrix, and stores the thresholdTh′ as the threshold matrix 108.

Th′=int(M_max×Th/(w×h))   (5)

On the other hand, if s=w×h does not hold, the processing proceeds toS1507 and “s” is updated with s+1, and then the processing returns toS1502.

According to S1201 to 1204 described above, the threshold matrix havinga dispersity characteristic as illustrated in FIG. 11 can be created foreach input tone.

In this case, if the variable lim is determined in such a manner thatany one of the high-dispersion tones is included in the search area forrecording data, the accumulated dot pattern for each recording scan canbe formed with a high dispersion. In the present exemplary embodiment,n=7, M0=0, M1=32, M2=64, M3=96, M4=128, MS=160, M6=192, M7=224, andM8=255 are set. In this case, when lim=16, any one of thehigh-dispersion tones is included in the search area for recording data,regardless of the size of image data obtained after color separation.Specifically, in a case where specific recording data withhigh-dispersion dot patterns is arranged at a regular interval ΔM (ΔM=32in the above example), when lim=ΔM/2 is set, any one of the specificrecording data can be included in the search area for recording data,regardless of image data obtained after color separation.

According to the present exemplary embodiment, a threshold matrix inwhich dot patterns are arranged with a high dispersion for specifictones can be created, unlike the case of determining dots one by onelike in the Void-and-Cluster method. Further, the variable lim isdetermined in such a manner that one of the specific tones is includedin a search area from M−lim to M+lim, thereby making it possible to formthe accumulated dot pattern with a high dispersion for each recordingscan.

Considering that a high-dispersion dot pattern is likely to be formedwhen a divisor of the size W×H of the threshold matrix of specificrecording data is set, the specific recording data M1 to Mn acquired inS1201 may be a divisor of the size W×H of the threshold matrix. Forexample, when the size W×H of the threshold matrix is 256×256, apower-of-two, such as 16, 64, or 256, may be set.

In the above exemplary embodiment, the method for determining therecording data M′ in the range from M−lim to M+lim has been described.However, the method for determining the recording data M′ is not limitedto this method. For example, the recording data M′ may be determined inan asymmetric range, such as a range from M−α to M+β. Further, thesearch area may be variable depending on the tone. The search area isnot particularly limited, and specific recording data closest to therecording data M in the image data D among the tones M1 to Mn may be setas M′ (however, it is preferable not to select the same recording dataM′ in different passes).

An example where the LUT in which the evaluation value for thedispersity of the dot pattern corresponding to each input tone is usedas the threshold matrix characteristic LUT 106 has been described above.However, the information held in the threshold matrix characteristic LUT106 is not limited to this example. For example, in the presentexemplary embodiment, only the values of M1 to Mn which have arelatively high dispersion may be stored. In this case, specificrecording data closest to the recording data M in the image data D amongthe tones M1 to Mn may be set as M′.

In the first and second exemplary embodiments, a case where ditheringusing the same threshold matrix for recording data for each recordingscan is executed has been described above by way of example. In a thirdexemplary embodiment, a case where different threshold matrices are usedfor each recording scan will be described by way of example.

FIGS. 15A, 15B, 15C, and 15D each illustrate a dispersity characteristicfor each tone for each of a plurality of threshold matrices used in thethird exemplary embodiment. FIGS. 15A, 15B, and 15C are each designed toform a dot pattern in which a high dispersion for a specific tone isobtained. FIG. 15A is used for dithering on recording data for therecording scan of the pass number 1. FIG. 15B is used for dithering onrecording data for the recording scan of the pass number 2. FIG. 15C isused for dithering on recording data for the recording scan of the passnumber 3. On the other hand, in FIG. 15D, optimization processing is notperformed on a specific tone and a threshold matrix is created in such amanner that all tones have substantially the same dispersity. Thethreshold matrix having the characteristic illustrated in FIG. 15D isused for dithering on nth recording data for a last recording scan. Thethreshold matrices desirably have such a relationship that exclusive dotpatterns are output in a low-frequency region and uncorrelated dotpatterns are output in a high-frequency region.

In the case of using a plurality of threshold matrices as describedabove, a plurality of threshold matrix characteristic LUTs is acquiredin S303. In the third exemplary embodiment, the threshold matrixcharacteristic LUTs corresponding to three threshold matrices except thethreshold matrix corresponding to the nth recording scan are acquired.

FIG. 16 is a flowchart of recording data setting processing according toa third exemplary embodiment. In S1601, the threshold matrixcharacteristic LUTs respectively corresponding to the first recordingscan to the (n−1)th recording scan are acquired. In this case, asillustrated in FIGS. 15A, 15B, 15C, and 15D, a plurality of tones forwhich dot patterns are set with a high dispersion is held in thethreshold matrices for each recording scan.

In S1602, image data obtained after color separation is equally dividedamong each of the recording scans, thereby setting the recording datafor each recording scan. In this case, the pixel value of each pixelconstituting the image data is multiplied by ¼, thereby dividing theimage data obtained after color separation.

In S1603, the recording data corresponding to the recording scans fromthe pass number 1 to the pass number 3 is updated with reference to thethreshold matrix characteristic LUTs acquired in S1602. This processingis executed by a method similar to the method used for the processingillustrated in FIG. 7.

In S1604, the recording data for the pass number 4 is calculated. Inthis case, the value obtained by subtracting the recording data for eachrecording scan from the image data obtained after color separation iscalculated as recording data M4′ for the pass number 4.

As described above, dithering may be performed using different thresholdmatrices for each recording scan. In each recording scan, the recordingdata for each recording scan is set with reference to the characteristicof the corresponding threshold matrix, thereby making it possible toform a dot pattern with a higher dispersity as a dot pattern for eachrecording scan.

Other Exemplary Embodiment

Some embodiments can also be implemented by processing in which aprogram for implementing one or more functions of the exemplaryembodiments described above is supplied to a system or apparatus througha network or storage medium, and one or more processors in a computer ofthe system or apparatus read out a program and execute the program. Someembodiments can also be implemented by a circuit (e.g., an applicationspecific integrated circuit (ASIC)) for implementing one or morefunctions.

Other Embodiments

Some embodiment(s) can also be realized by a computer of a system orapparatus that reads out and executes computer-executable instructions(e.g., one or more programs) recorded on a storage medium (which mayalso be referred to more fully as a ‘non-transitory computer-readablestorage medium’) to perform the functions of one or more of theabove-described embodiment(s) and/or that includes one or more circuits(e.g., application specific integrated circuit (ASIC)) for performingthe functions of one or more of the above-described embodiment(s), andby a method performed by the computer of the system or apparatus by, forexample, reading out and executing the computer-executable instructionsfrom the storage medium to perform the functions of one or more of theabove-described embodiment(s) and/or controlling the one or morecircuits to perform the functions of one or more of the above-describedembodiment(s). The computer may comprise one or more processors (e.g.,central processing unit (CPU), micro processing unit (MPU)) and mayinclude a network of separate computers or separate processors to readout and execute the computer-executable instructions. Thecomputer-executable instructions may be provided to the computer, forexample, from a network or the storage medium. The storage medium mayinclude, for example, one or more of a hard disk, a random-access memory(RAM), a read-only memory (ROM), a storage of distributed computingsystems, an optical disk (such as a compact disc (CD), digital versatiledisc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memorycard, and the like.

While the present disclosure has described some exemplary embodiments,it is to be understood that the claims are not limited to the disclosedexemplary embodiments. The scope of the following claims is to beaccorded the broadest interpretation so as to encompass all suchmodifications and equivalent structures and functions.

This application claims priority to Japanese Patent Application No.2017-187010, which was filed on Sep. 27, 2017 and which is herebyincorporated by reference herein in its entirety.

What is claimed is:
 1. An image processing apparatus for forming animage by superimposing n (n≥2) records on a same region in a recordingmedium, the image processing apparatus comprising: a holding unitconfigured to hold threshold matrix information related to a thresholdmatrix characteristic representing a dispersity of a dot pattern of eachtone value obtained when dithering is performed using a thresholdmatrix; a setting unit configured to set recording data indicating anamount of recording for n recording scans by dividing image data for then recording scans based on the threshold matrix information; and ahalftoning unit configured to perform dithering using the thresholdmatrix on the recording data for each of the n records.
 2. The imageprocessing apparatus according to claim 1, wherein the setting unitequally divides pixel values of respective pixels in an image indicatedby the image data into n values, and then updates at least one piece ofrecording data for the n recording scans based on the threshold matrixcharacteristic.
 3. The image processing apparatus according to claim 2,wherein the setting unit sets a search area to recording data for arecording scan to be processed among the n recording scans, anddetermines whether a tone with a highest dispersity in the search areais present in the threshold matrix characteristic, and when the tonewith the highest dispersity is present, the setting unit updatesrecording data for the recording scan to be processed with the tone withthe highest dispersity.
 4. The image processing apparatus according toclaim 2, wherein the setting unit updates the recording data based onthe threshold matrix characteristic for recording scans up to an (n−1)threcording scan except an nth recording scan.
 5. The image processingapparatus according to claim 1, wherein the holding unit holds, as thethreshold matrix information, a dispersity evaluation value for eachtone of the threshold matrix, and the setting unit sets the recordingdata with reference to the dispersity evaluation value for each tone ofthe threshold matrix.
 6. The image processing apparatus according toclaim 1, wherein the threshold matrix is a matrix in which thresholds ofdifferent values are arranged to obtain a high-dispersion dot patternfor a plurality of tones set at predetermined intervals.
 7. The imageprocessing apparatus according to claim 1, wherein the threshold matrixincludes a blue noise characteristic.
 8. The image processing apparatusaccording to claim 2, wherein the setting unit does not update recordingdata corresponding to a last recording scan among the n recording scans.9. The image processing apparatus according to claim 3, wherein thesearch area is set to 5% to 10% of a range of pixel values in the imagedata.
 10. The image processing apparatus according to claim 1, whereinthe threshold matrix is a matrix created by a Void-and-Cluster method.11. The image processing apparatus according to claim 1, wherein thehalftoning unit converts each piece of recording data into binary data.12. The image processing apparatus according to claim 1, wherein theholding unit holds pieces of threshold matrix information respectivelycorresponding to a plurality of threshold matrices.
 13. The imageprocessing apparatus according to claim 1, wherein the halftoning unitselects any one of the plurality of threshold matrices for each of thepieces of recording data, and performs halftoning on the selectedthreshold matrix.
 14. The image processing apparatus according to claim1, wherein the halftoning unit generates constraint information based onhalf-tone image data obtained by performing halftoning on the recordingdata, and refers to the constraint information generated based on thehalf-tone image data corresponding to a recording scan preceding atarget recording scan when halftoning is performed on the recording datafor the target recording scan among the n recording scans.
 15. The imageprocessing apparatus according to claim 14, wherein the constraintinformation is information having a correlation with a possibility thata dot is already located at the same location in the preceding recordingscan.
 16. The image processing apparatus according to claim 14, whereinthe halftoning unit determines, for a pixel of interest in the recordingdata corresponding to the target recording scan, a halftoning result forthe pixel of interest based on the constraint information correspondingto the pixel of interest, a threshold corresponding to the pixel ofinterest in the threshold matrix, and the recording data correspondingto the pixel of interest.
 17. The image processing apparatus accordingto claim 16, wherein the halftoning unit turns off a dot correspondingto the pixel of interest when the constraint information correspondingto the pixel of interest is greater than the threshold corresponding tothe pixel of interest.
 18. The image processing apparatus according toclaim 17, wherein the halftoning unit compares the recording datacorresponding to the pixel of interest with the threshold when theconstraint information corresponding to the pixel of interest is smallerthan the threshold corresponding to the pixel of interest, and thehalftoning unit turns on the dot corresponding to the pixel of interestwhen the recording data corresponding to the pixel of interest isgreater than the threshold corresponding to the pixel of interest.
 19. Anon-transitory computer-readable storage medium storing a program tocause a computer to perform an image processing method for an imageprocessing apparatus to form an image by superimposing n (n≥2) recordson a same region in a recording medium, the method comprising: holdingthreshold matrix information related to a threshold matrixcharacteristic representing a dispersity of a dot pattern of each toneobtained when dithering is performed using a threshold matrix; settingrecording data for n recording scans by dividing image data for the nrecording scans based on the threshold matrix information; andperforming dithering using the threshold matrix on the recording datafor each of the n records.
 20. An image processing method for forming animage by superimposing records on a same region in a recording medium,the method comprising: holding threshold matrix information related to athreshold matrix characteristic representing a dispersity of a dotpattern of each tone obtained when dithering is performed using athreshold matrix; setting recording data for n recording scans bydividing image data for the n recording scans based on the thresholdmatrix information; and performing dithering using the threshold matrixon the recording data for each of the n records.